Concept for the Architecture of a Self-Learning Engineering Assistance System

Year: 2010
Editor: Andreas Dagman; Rikard Söderberg
Author: Sebastian Röhner; Georg Gruber; Sandro Wartzack
Section: Virtual Product Realization
Page(s): 205-216


Considerable efforts have been taken in the past decades to integrate design and manufacturing knowledge into the product development process. A common approach is to offer designers the support of knowledge based systems, expert systems or assistance systems. There are several methodologies of these systems which differ in representing and reasoning of knowledge. Keeping their knowledge base up to date is a crucial, yet demanding issue. Currently most means of knowledge acquisition are labour-intensive for knowledge engineers and domain experts. Thus, the knowledge acquisition process is often the bottleneck, and automatic knowledge acquisition from databases is a promising approach to overcome it. In this paper a concept for the architecture of a self-learning engineering assistance system is presented, that uses data mining methods for the acquisition, updating and reasoning of knowledge.

Keywords: artificial intelligence, data mining, assistance system

Please sign in to your account

Cookies help us deliver our services. By using our services, you agree to our use of cookies.  

Join Now!